Apparatus and method for determining GPS tracking loop parameter based on SNR estimation

Abstract

A method for estimating signal quality of a spread spectrum signal is provided. The method includes squaring a plurality of in-phase correlation results and a plurality of quadrature correlation results, summing each squared in-phase correlation result and the corresponding correlation result to obtain a plurality of sum-of-square values, detecting a peak value among the plurality of sum-of-square results, calculating an average of non-peak values among the plurality of sum-of-square results. The peak value is regarded as a signal power value, while the averaged non-peak values are regarded as an average noise power value. A signal-to-noise ratio is then calculated based on the signal power value and the average noise power value. A method for determining the parameters for the tracking loop is also provided. The method includes estimating the signal-to-noise ratio of the spread spectrum signal, and determining the tracking loop parameters based on the signal-to-noise ratio.

1. A method for estimating a signal-to-noise ratio of a spread spectrum signal, the spread spectrum signal being digitized at a predetermined frequency, the method comprising:
 receiving the spread spectrum signal in a receiver, the spread spectrum signal having an in-phase component and a quadrature component; 
 receiving a predetermined pseudorandom code from a code generator; 
 determining an in-phase correlation result based on the in-phase component and a predetermined pseudorandom code over a time period; 
 determining a quadrature correlation result based on the quadrature component and the predetermined pseudorandom code over the time period; 
 determining a signal power value based on the in-phase correlation result and the quadrature correlation result; 
 determining an average noise power value based on the in-phase component and the quadrature component, wherein the in-phase component being a digital signal having a plurality of data points within the time period, the quadrature component being a digital signal having a plurality of data points within the time period, the average noise power value being determined by
 squaring each data point of the in-phase component; 
 calculating a first mean among the squared data points of in-phase component; 
 squaring each data point of the quadradure component; 
 calculating a second mean among the squared data points of quadrature component; and 
 summing the first mean and the second mean to obtain the average noise power value; and 
 
 determining in a SNR estimation module the signal-to-noise ratio based at least on the signal power value and the average noise power value. 
 
     
     
       2. The method of  claim 1 , wherein the step of determining the signal power value comprising:
 squaring the in-phase correlation result and the quadrature correlation result; and 
 summing the squared value of in-phase correlation result and the squared value of quadrature correlation result to obtain a signal power value. 
 
     
     
       3. The method of  claim 1 , wherein the step of determining the signal-to-noise ratio further comprising:
 multiplying the average noise power value and a number of data points within the time period to obtain a total average noise power value over the time period; 
 subtracting the total average noise power value from the signal power value to obtain a desired signal power value; and 
 dividing the desired signal power value by the total average noise power value to obtain the signal-to-noise ratio. 
 
     
     
       4. The method of  claim 1 , wherein the predetermined pseudorandom code having substantially the same phase shift with a pseudorandom code spreading the spread spectrum signal. 
     
     
       5. The method of  claim 1 , wherein the predetermined pseudorandom code being a prompt pseudorandom code generated by a code generator in a code tracking loop during tracking stage in spread spectrum signal processing. 
     
     
       6. The method of  claim 1 , further comprising filtering the signal-to-noise ratio to obtain a smooth signal-to-noise ratio. 
     
     
       7. The method of  claim 6 , wherein the filtering further comprising providing a Kalman filter to perform the filtering.